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Goals programming multiple linear regression model for optimal estimation of electrical engineering staff according to load Demand | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، Special Issue، اسفند 2021، صفحه 123-132 اصل مقاله (373.61 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.4917 | ||
| نویسندگان | ||
| Shrook A. S. Al-Sabbah1؛ Zainab Hassan Radhy* 2؛ Hayder Al Ibraheemi3 | ||
| 1Department of Statistics, Administration and Economic College, Karbala University, Iraq. | ||
| 2College of computer science and information technology - University of Al-Qadisiyah - Iraq. | ||
| 3Faculty of Technical Engineering/Islamic University-Iraq. | ||
| تاریخ دریافت: 30 مهر 1399، تاریخ بازنگری: 23 دی 1399، تاریخ پذیرش: 22 بهمن 1399 | ||
| چکیده | ||
| The linear multiple regression model is one of the prediction models whose parametric estimations could be achieved in different methods. Ordinary Least Square error (OLS) is most popular in this field of application. Although it could accurately achieve the estimation task, it fails in processing the multiple objective models. From the other side of view, the load demand for electrical energy continuously rises around the world. The governments always tackle the increase in electrical load demanding by establishing more electrical power plants and more power distribution directories. Future prediction for several electrical engineers to manage and provide technical supports for these plants and directories becomes, nowadays, urgent. This paper addresses the estimating drawback of OLS by employing the Goals Programming (GP) in the field of parametric estimation. The validity of the proposed method was applied to estimating the required number of electrical engineers, in the next coming years, as the electrical load considerably increases. Thereby, the GP was used, in this work, to determine the best linear representation for a set of data. The obtained results proved that the (GP) method is more flexible and efficient in dealing with such subject area especially in the case of multiple objective models. | ||
| کلیدواژه‌ها | ||
| Linear multiple module؛ Goals programming method؛ least-square error؛ Electrical | ||
| مراجع | ||
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[1] M. H. Ahmad and et al, “Comparing Least-Squares and Goal Programming Estimates of Linear Regression Parameters,” MATEMATICA, vol. 21, no. 2, (2005) 101–112. [2] A. Charne and W. Cooper, “Management Models and Industrial Application of Linear Programming,” Manage. Sci., vol. 4, no. 1, (1957). [3] A. Charne and W. Cooper, “Goal Programming and Multiple Objectives Optimizations.,” Eur. J. Oper. Res., vol. 1, (1977) 39–54. [4] L. AL.Degelae, ”Building the workforce planning model in the General Establishment for Electricity Distribution of Baghdad,” PhD thesis, Mustansiriya University, (1997).[5] J. Ignazio, Goal Programming and Extensions, 2nd ed. Lexington Books, (1976). [6] Y. Ijiri, “Management Goals and Accounting for Control,” Stud. Math. Manag. Econ., vol. 3, (1965). [7] S. Kathem, “Comparisons between parameter estimations of linear regression model using OLS and programming goals,” J. of Administration and Econ. Al Muthana Univ., (2009). [8] E. Tu, “A Comparison of Three Linear Programming Models for Computing Least Absolute Values Estimates,” J.OF Math .and Stat, vol. 34, (2005) 95–102. [9] D. A. Wolfe, ”Nonparametrics: Statistical Methods Based on Ranks and Its Impact on the Field of Non-parametric Statistics,” Sel. Work. E. L. Lehmann, (2012) 1101–1110. | ||
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